GPU and Parallel Programming

Learning Goals

A successful candidate to this course learns a series of best practices forthe development of efficient parallel codes, capable to exploit a distributed multi-core platform for HPC, equipped with add-on accelerators, including being able to effectively analyze the performance of parallel code.
She/he will be able to analyze the main computational aspects of a given problem, implementing scalable and efficient strategies of parallelization.

Program in pills

Best practices of efficient parallel and GPU programming for HPC. Advanced programming for modern high-end systems for HPC. Performance analysis of parallel applications.

Area

Computer Science and Intensive Computing

Curriculum Foundations
TAF Type

Curriculum Industry
TAF Type

D

Curriculum Health
TAF Type

Curriculum Economy
TAF Type

SSD

INF/01

ECTS

6

Semester

Lecturers